menu – Virag Consulting

Agent Support for Menu Selling

As a software guy, I am always surprised to find F&I trainers doing generic menu training without attention to the specific menu system used in the dealership. There is some generic advice, which I covered in Best Practices for Menu Selling, but then your client’s next question is going to be: “How do I do that on Darwin?” Or Maxim. Or Tekion.

Controlling the menu means you control what products are on it, and how they’re presented.

Familiarity with the given menu system is even more important when you represent a provider or agent. Now, you’re not only training how to sell product, but to sell your product. As I told my boss at Safe-Guard, “you can put a gun to the guy’s head but if your product isn’t on the menu, he’s not selling it.”

And we have seen exactly this. “We don’t sell your coverage because it’s a lease deal.” Because it’s preowned. Because it’s highline. By “we,” I mean Safe-Guard’s ace menu trainer, Michele McMinn, and the menu support team we put together. Double your penetration with this one weird trick…

The easiest way to do this is to pay for the dealer’s menu system. Then, your trainers only have to be experts in one system, and you have a hotline to their tech support department.

Controlling the menu means you control what products are on it, and how they’re presented. If your dealer base is too diverse for that, then you will have to develop F&I trainers who are expert in all of them.

Setting Up the Menu Support Team

You also have to make sure your products are compatible with certain standards used by PEN and the menu-system community. If this is news to you, you’re not alone. Even in the year 2025, I still find providers and agents who think their product is a piece of paper.

Just because the art department added a checkbox for “Rebate” or “Sagittarius,” doesn’t mean that checkbox is going anywhere unless you know a little something about the PEN interface standards. Here’s what a good menu support team looks like:

Trainers who are rated on more than one menu system, in addition to generic F&I training.
Dedicated support, so the trainers can reach someone while they’re in the dealership. This is key. The menu support desk also looks for recurring issues and develops a knowledge base.
Tech people who can run tools like Postman and XML Spy and, ideally, get involved with coding on your menu-system API (the interface that PEN uses).

At Safe-Guard, I went so far as to hire a Product Manager to own the API and to liaise with PEN and the menu-system community.

Designing menu-friendly products starts at the very beginning, when the coverage product manager meets with my product manager. Let’s say you want to offer Tire, Key, and Dent on the same form. Do you want all seven possible combinations? What about the “cosmetic” upcharge?

It’s not enough to have the right boxes on the form. You need to think about how the product will flow through PEN, and how it will look on Darwin. And Maxim. And Tekion.

It’s not enough to have the right boxes on the form. You need to think about how it will look on Darwin.

You can see how this is a team effort. If your product is making the menu choke, support needs to run that issue back to the programmers. If your trainer isn’t rated on that menu, she shouldn’t be in that store.

By the way, you should keep track of which DMS, which menu, and which sales process is used in each store. Keep track of those, along with the training sessions, after-action reports, and your (rapidly improving) penetration scores.

When Michele and I started playing this game at a high level, we discovered we were competing with JM&A. That was it. Everyone else was unarmed.

Moving to Powersports

Back in 2020, I contacted all the leading F&I administrators, pitching my plan for AI-priced service contracts. As soon as the conversation touched on VIN decoding, they would invariably stop and ask me if I could get VIN data for powersports. This turned out to be a trend.

Having been in automotive for many years, I was a little sniffy about powersports – although I had worked with Ducati, Harley, and RumbleOn during my tenure at Safe-Guard. What I knew then was that powersports had only one DMS (Lightspeed), one menu system (Maxim), and no – there was no good VIN service.

When you’re in the powersports industry, you’re selling fun.

At $34 billion, powersports is dwarfed by the mighty auto market, but it has higher margins and better growth. According to published financials, gross profit is around 20% for auto retail and 30% for powersports. I expect that the 3% CAGR will perk up as the ecosystem improves, which is the topic of today’s post.

In automotive, we have a rich software ecosystem. In powersports, not so much. The ecosystem is complicated by a wide array of vehicles, from jet skis to snowmobiles, with the attendant challenges in standard process and vehicle ID.

The Powersports Market

There are roughly 17,000 car dealers in America, compared to 7,000 motorcycle dealers. From a dealer’s perspective, powersports means less competition and higher margins, according to Mercer Capital – and it is terra nova for software vendors, as well. Public auto group Sonic took Mercer’s advice, recently acquiring 13 powersports dealerships.

Here is another explainer, this one from SEMA, on the market structure of ATVs, UTVs, and motorcycles. I am including it basically for this great quote from dealer consultant Rob Greenwald. “When you’re in the powersports industry, you’re selling fun,” he said. “We sell lifestyle.”

Unlike buying a car, a powersports purchase is discretionary. This means it’s more susceptible to economic downturns, but it’s also more fun. People enjoy visiting the dealership, and that changes the technology model.

Digital retail, for example, is still important – but not to reduce time in the dealership. It’s so that we don’t have to pull you out of that RZR to sign papers.

Crossover Software Vendors

A few of the website providers I wrote about are also active in powersports, like Dealer Inspire and Fox. However, neither of these seems to have their digital retail solution in play. One DR vendor that I recognize from auto is Joydrive, which made a strong entrance by partnering with Polaris and Octane.

Octane is the leading finance source in powersports, but there is a new entrant from the auto space, RouteOne founder Toyota Financial. TFS is now the private label consumer and wholesale finance source for Bass Pro.

Another crossover vendor is Darwin which, after dominating the auto space, moved first into motorcycles – challenging Maxim’s lock on Harley-Davidson – and now into other powersports. Speaking of menu selling, F&I providers here are Galt, Safe-Guard, and Protective.

Movement Toward Powersports

What I encountered in 2020 seems to have been a general movement toward powersports. Lured by big groups like Bass Pro with its 170 locations, Marine Max (125), and RumbleOn (60), software vendors are extending into powersports.

There sure are a lot of motorcycles at this car show.

They will go where the dealers are and, as I walked the NADA show in Dallas, I had to smile at the untapped demand. “Drop your business card and win this Harley,” offered one vendor.

“There sure are a lot of motorcycles at this car show,” I remarked. And then there was the Kawasaki booth, enlisting car dealers looking to diversify – for fun and profit.

Schrödinger’s Combo Product

NADA has recently published a model policy for properly selling F&I products, i.e., without running afoul of the Attorney General. It includes the disclosure formerly known as the AutoNation Pledge, and a new procedure which seems to be taking the place of the old-school waiver form. I say “seems” because there is no mention of the old form, which I believe has something to do with nuclear physicist Erwin Schrödinger.

Prior to the sale of a VPP, the Dealership will request the customer’s acknowledgement of the election to purchase or decline each selected VPP or VPP bundle.

As everyone knows, subatomic particles exist in an indeterminate state until they are pinned down by measurement. For example, if you have a radioactive isotope of Cesium, you can’t tell whether it has decayed until you aim your Geiger counter at it. Not only can you not tell what state the atom is in, it is not definitely in any state until you measure it.

To show how this contrasts with traditional physics, Schrödinger proposed the following thought experiment. Imagine there is a cat in a box with the Cesium rigged to kill the cat when it decays. According to the Uncertainty Principle, the cat is both alive and dead at the same time.

Similarly, the F&I waiver requires each product to be either accepted or declined. You bought the dent protection, so it prints in the green column, but you turned down roadside assistance. It prints in the red column. To save a few dollars, you are willing to leave your family stranded. Please sign here to confirm.

But what if dent and roadside – and key and windshield – are part of the same bundle? You only bought one of the components, so it would be misleading to print it in the green column. On the other hand, you are not going to confirm declining the bundle, because you did buy part of it. So, in which column does this product belong?

Here are some ideas:

The menu system should account for the child products and print them individually on the waiver. It should also count them separately as product sales.
The menu system should print the coverage description, and the coverage description should state which components were accepted.
Providers should offer bundles all or nothing, and not allow them to be split up.

Unlike Schrödinger, you will not win the Nobel Prize for solving this one – but you can provide some guidance to your fellow F&I practitioners. Click the link below to register your answer.

Analytics for Menu Presentation

Last week, I presented a single-column format for menu selling on an iPhone, with the glib recommendation to let analytics determine the sort order. Today, I will expand on that. Our task is to sort the list of products in descending order of their relevance to the current deal, which includes vehicle data, consumer preferences, and financing terms.

This sorting task is the same whether we are flipping through web pages or scrolling down the mobile display. The framework I present here is generalized and abstract, making the task better suited to automation, but ignoring the specific F&I knowledge we all take for granted. I’ll come back to that later.

For now, let’s assume we have six products to present, called “Product One,” and so on, and four questions that will drive the sorting. Assume these are the usual questions, like, “how long do you plan on keeping the car?”

That answer will be in months or years, and the next one might be in miles, but we are going to place them all on a common scale from zero to one (I warned you this would be abstract). Think of using a slider control for each input, where the labels can be anything but the range is always 0.0 to 1.0.

Next, assign four weights to each product, representing how relevant each question is for that product. The weights do not have to be zero to one, but I recommend keeping them all around the same starting magnitude, say 1 to 5. Weights can also be negative.

For example, if there’s a question about loan-to-value, that’s important for GAP. High LTV will correlate positively with GAP sales. If you word that question the other way, the correlation will still be strong, but negative. So, now you have a decision matrix that looks something like this:

Yes, we are doing weighted factor analysis. Let’s say that, for a given deal, the answers to our four questions are, in order:

[0.3, 0.7, 0.1, 1.0]

To rank the products for this deal we simply multiply the decision matrix by the deal vector. I have previously confessed my weak vector math skills, but Python has an elegant way to do this.

Product Two ranks first, because of its affinity for high-scoring Question Four. Product Four takes second place, thanks to the customer’s response to Question Two – whatever that may be. By now, you may have noticed that this is the setup for machine learning.

If you are blessed with “big data,” you can use it to train this system. In a machine learning context, you may have hundreds of data points. In addition to deal data and interview questions, you can use clickstream data, DMS data, contact history, driving patterns (?) and social media.

If not, you will have to use your F&I savvy to set the weights, and then adjust them every thousand deals by manually running the numbers.

For example, we ask “how long will you keep the car?” because we know when the OEM warranty expires. Given make, model, and ten thousand training deals, an AI will dope out this relationship on its own. We can do it manually by setting one year past the warranty as 0.1, two as 0.2, etc. We can also set a variable indicating how complete the manufacturer’s coverage is.

Same story with GAP. Give the machine a loan amount and a selling price, and it will “discover” the correlation with GAP sales. If setting the weights manually, set one for LTV and then calculate the ratio for each deal.

Lease-end protection, obviously, we only want to present on a lease deal. But we don’t want it to crowd out, say, wearables. So, weight it appropriately on the other factors, but give it big negative weights for cash and finance deals.

I hope this gives some clarity to the analytics approach. In a consumer context, there is no F&I manager to carefully craft a presentation, so some kind of automation is required.